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Enregistrement W6945121811 · doi:10.24442/boristheses.1848

Zika virus: causality, open science and risk of emerging infectious diseases

2020· dissertation· en· W6945121811 sur OpenAlexfundno aff

Notice bibliographique

RevueBORIS Theses (Bern Open Research Information System) (Bern University Library, Hochschulstrasse 6, 3012 Bern, Switzerland) · 2020
Typedissertation
Langueen
DomaineMedicine
ThématiqueMosquito-borne diseases and control
Établissements canadiensnon disponible
Organismes subventionnairesCenters for Disease Control and PreventionUniversité LavalFundação Oswaldo CruzWorld Health OrganizationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Institutes of HealthNational Science Foundation
Mots-clésZika virusOutbreakDiseaseMicrocephalyEpidemiologyAsymptomaticTransmission (telecommunications)

Résumé

récupéré en direct d'OpenAlex

The Zika virus (ZIKV) outbreak in the Americas between 2015 and 2017 took the world by surprise. Within two years, over 1.5 million suspected or confirmed cases were reported. However, the true incidence is likely much higher, due to under-reporting and asymptomatic infections that are undetected. As of July 2019, 87 countries had reported ongoing or past circulation of ZIKV. ZIKV infection results generally in mild and transient symptoms. The disease caused by ZIKV is often asymptomatic or mild. However, infection during pregnancy can result in severe adverse congenital outcomes with microcephaly as most prominent. This was first noted in clusters of infants born with disabilities linked to ZIKV infection in Brazil in 2015, making ZIKV a disease with a serious public health impact. In this thesis, I explore different aspects of the ZIKV epidemic. I use different epidemiological methods to provide insight in the Zika virus as a cause of adverse outcomes, ZIKV as a sexually transmitted disease and the risk of future ZIKV outbreaks. In Chapter 1, I provide an introduction to the history of emerging infections and the emergence of ZIKV specifically. I describe the investigation of causality, the use and accumulation of evidence during disease outbreaks, and how disease transmission can be investigated using mathematical models. In Chapter 2, I provide insight in how evidence accumulates during an outbreak and more in general during new causal questions. Case reports and case series were the first studies to appear, followed by basic research (in vivo and in vitro studies). It took more than a year after the onset of the ZIKV outbreak for robust epidemiological studies to be published. Establishing early public health guidance thus requires a broad approach taking into account all evidence available. We have to make do with the low quality evidence. To minimize further delays, evidence should be accessible as soon as it becomes available through rapid and open access dissemination. In Chapter 3, I extend a systematic review that was conducted earlier, and turn it into a living systematic review. I introduce the concept and implementation of living systematic reviews in the context of an emerging disease. I assess the evidence on the causal relation between ZIKV infection and adverse congenital and auto-immune neurological outcomes, published between May 30, 2016 and January 18, 2017, using a framework based on the causality dimensions of Bradford Hill. During this period, the evidence expanded that ZIKV was indeed a cause of congenital abnormalities and Guillain-Barré syndrome (GBS). I provide a proof of concept for the use of living systematic reviews to synthesize evidence about an emerging pathogen such as ZIKV. In Chapter 4, I assess the evidence published between January 18, 2017 and July 1, 2019. I quantify the strength of association of the relation between maternal ZIKV infection and congenital adverse outcomes and between ZIKV infection and GBS. I found that the strength of association between ZIKV infection and adverse outcomes from case-control studies differs according to whether exposure to ZIKV is assessed in the mother (odds ratio (OR) 3.8, 95% CI: 1.7–8.7, I2=19.8%) or the foetus/infant (OR 37.4, 95% CI: 11.0–127.1, I2=0%). In cohort studies, the risk of congenital abnormalities was 3.5 times higher after ZIKV infection (95% CI: 0.9–13.5, I2=0%). The strength of association between ZIKV infection and GBS was higher in studies that enrolled controls from hospital (OR: 55.8, 95% CI: 17.2-181.7, I2=0%) than in studies that enrolled controls at random from the same community or household (OR: 2.0, 95% CI: 0.8–5.4, I2=74.6%). The heterogeneity between the studies could be partly explained by the heterogeneity in methods and sampled populations. Studies suffered from bias and uncontrolled residual confounding. In Chapter 5, I present a framework to systematically assess the evidence for ZIKV as a sexually transmitted disease. I reviewed all available literature and concluded that the risk of sexual transmission of ZIKV is likely small, but relevant for certain risk groups. I found that in semen viral RNA could be detected for a median period of 34 days (95% CI: 28–41 days) and 35 days (no CI given) based on two cohort studies. Aggregated data about detection of ZIKV RNA from 37 case reports and case series indicate a median duration of 40 days (95% CI: 30–49 days) and a maximum duration of 370 days in semen. In human vaginal fluid, the median duration was 14 days (95% CI: 7–20 days) and the maximum duration was 37 days. Infectious virus in human semen was detected for a median duration of 12 days (95% CI: 1–21 days) and a maximum of 69 days. I highlight the poor quality of the evidence and the need for systematic observational studies that evaluate the risk of sexual transmission of ZIKV. In Chapter 6, I present predictions on the future risk of ZIKV, based on data from Managua, Nicaragua, using mathematical modelling. The risk of a new outbreak in the next decades is low due to herd immunity. However, a next outbreak will disproportionally hit people in the young reproductive age hardest (age 15–29 years). Vaccination could curb this risk: Early introduction of vaccination in 15-year-old girls has the capacity to extend the herd immunity and be of benefit to the whole population. Introduction of a vaccine needs to happen within a decade after the 2016 outbreak to achieve this protection. The duration of immunity following ZIKV infection has impact on the speed at which outbreaks will reoccur. In Chapter 7, I present an overview of the main findings and I discuss the interpretation and implications of these results. I discuss the strengths and limitations of the work, and outline follow-up questions emerging from the work. In this thesis, I establish and use different frameworks and methods that help to make sense of the limited evidence that is available during disease outbreaks. ZIKV has been introduced on the American continent, and it is likely there to stay, thus we have to accept that ZIKV will continue to re-emerge. At the same time, due to the climate change, the European temperate region also becomes more suitable for vector-borne disease such as ZIKV. With the ZIKV epidemic on the wane, we now have time to consolidate findings and implement the lessons learnt. We need to be prepared for the re-emergence of ZIKV but also for the emergence of new diseases. The tools and methods I present in this thesis, will help us to be more prepared for a next outbreak.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,036
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesScience ouverte
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,999
Score d'incertitude au seuil0,047

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,036
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,004
Communication savante0,0060,006
Science ouverte0,0010,003
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,029
Tête enseignante GPT0,317
Écart entre enseignants0,287 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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